Applying Artificial Intelligence (AI) into manufacturing in the context of Industry 5.0 (I5.0) provides for enhancing quality control of processes. This paper employs real life data of mould manufacturing process with the objective of developing a tool for controlling and predicting quality of manufactured highly technically demanding product used for the air conditioning of the high-end cars. Firstly, the parameters that affect the quality level of the manufactured end products, namely compressor were defined. Next, the values of these parameters were collected and pre-processed from IoT-based sensors and the Enterprise Resource Planning (ERP) system during the execution of an order within one month. In total, 9919 real data relating to the die castings process for the selected product was received. Secondly, this study applies Artificial Neural Network (ANN) to develop an AI-based classifier of the quality level of manufactured parts. Finally, AI-driven data analytics model was developed and verified. The accuracy was achieved in the training and testing phases 98.62% and 98.94% respectively. Additionally, this study develops the approach to simulate of process parameter value changes for improving the quality level of manufactured parts. This is a universal AI-driven IoT Monitoring System (AIMS) for industry supporting proactive management.